Figure REF A shows the accuracy of each method's computation of \(p^*_{ik}\) . Each gray line plots the accuracy of each method for a single \(\mathcal {B}^\text{FDSM}\) , while the red line plots the mean accuracy of each method over all 384 \(\mathcal {B}^\text{FDSM}\) . We find that choosing \(p^*_{ik}\)  using a logistic regression with an interaction term (i.e., (Scobit-I and Logit-I)) is on average least accurate,[1]}, [2]} while choosing \(p^*_{ik}\)  using entropy maximization (i.e., BiCM and Poly) is on average most accurate.[3]}, [4]}
